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mainSift.cpp
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mainSift.cpp
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//********************************************************//
// CUDA SIFT extractor by Marten Björkman aka Celebrandil //
// celle @ csc.kth.se //
//********************************************************//
#include <iostream>
#include <cmath>
#include <iomanip>
#include <opencv2/core/core.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/imgproc/imgproc.hpp>
#include "cudaImage.h"
#include "cudaSift.h"
int ImproveHomography(SiftData &data, float *homography, int numLoops, float minScore, float maxAmbiguity, float thresh);
void PrintMatchData(SiftData &siftData1, SiftData &siftData2, CudaImage &img);
void MatchAll(SiftData &siftData1, SiftData &siftData2, float *homography);
double ScaleUp(CudaImage &res, CudaImage &src);
///////////////////////////////////////////////////////////////////////////////
// Main program
///////////////////////////////////////////////////////////////////////////////
int main(int argc, char **argv)
{
int devNum = 0;
if (argc>1)
devNum = std::atoi(argv[1]);
// Read images using OpenCV
cv::Mat limg, rimg;
cv::imread("data/left.pgm", 0).convertTo(limg, CV_32FC1);
cv::imread("data/righ.pgm", 0).convertTo(rimg, CV_32FC1);
unsigned int w = limg.cols;
unsigned int h = limg.rows;
std::cout << "Image size = (" << w << "," << h << ")" << std::endl;
// Initial Cuda images and download images to device
std::cout << "Initializing data..." << std::endl;
InitCuda(devNum);
CudaImage img1, img2;
img1.Allocate(w, h, iAlignUp(w, 128), false, NULL, (float*)limg.data);
img2.Allocate(w, h, iAlignUp(w, 128), false, NULL, (float*)rimg.data);
img1.Download();
img2.Download();
// Extract Sift features from images
SiftData siftData1, siftData2;
float initBlur = 1.0f;
float thresh = 3.5f;
InitSiftData(siftData1, 32768, true, true);
InitSiftData(siftData2, 32768, true, true);
// A bit of benchmarking
for (thresh=1.00f;thresh<=4.01f;thresh+=0.50f) {
for (int i=0;i<10;i++) {
ExtractSift(siftData1, img1, 5, initBlur, thresh, 0.0f, false);
ExtractSift(siftData2, img2, 5, initBlur, thresh, 0.0f, false);
}
// Match Sift features and find a homography
for (int i=0;i<1;i++)
MatchSiftData(siftData1, siftData2);
float homography[9];
int numMatches;
FindHomography(siftData1, homography, &numMatches, 10000, 0.00f, 0.80f, 5.0);
int numFit = ImproveHomography(siftData1, homography, 5, 0.00f, 0.80f, 3.0);
std::cout << "Number of original features: " << siftData1.numPts << " " << siftData2.numPts << std::endl;
std::cout << "Number of matching features: " << numFit << " " << numMatches << " " << 100.0f*numFit/std::min(siftData1.numPts, siftData2.numPts) << "% " << initBlur << " " << thresh << std::endl;
}
// Print out and store summary data
PrintMatchData(siftData1, siftData2, img1);
cv::imwrite("data/limg_pts.pgm", limg);
// Free Sift data from device
FreeSiftData(siftData1);
FreeSiftData(siftData2);
}
void MatchAll(SiftData &siftData1, SiftData &siftData2, float *homography)
{
#ifdef MANAGEDMEM
SiftPoint *sift1 = siftData1.m_data;
SiftPoint *sift2 = siftData2.m_data;
#else
SiftPoint *sift1 = siftData1.h_data;
SiftPoint *sift2 = siftData2.h_data;
#endif
int numPts1 = siftData1.numPts;
int numPts2 = siftData2.numPts;
int numFound = 0;
for (int i=0;i<numPts1;i++) {
float *data1 = sift1[i].data;
std::cout << i << ":" << sift1[i].scale << ":" << (int)sift1[i].orientation << std::endl;
bool found = false;
for (int j=0;j<numPts2;j++) {
float *data2 = sift2[j].data;
float sum = 0.0f;
for (int k=0;k<128;k++)
sum += data1[k]*data2[k];
float den = homography[6]*sift1[i].xpos + homography[7]*sift1[i].ypos + homography[8];
float dx = (homography[0]*sift1[i].xpos + homography[1]*sift1[i].ypos + homography[2]) / den - sift2[j].xpos;
float dy = (homography[3]*sift1[i].xpos + homography[4]*sift1[i].ypos + homography[5]) / den - sift2[j].ypos;
float err = dx*dx + dy*dy;
if (err<100.0f)
found = true;
if (err<100.0f || j==sift1[i].match) {
if (j==sift1[i].match && err<100.0f)
std::cout << " *";
else if (j==sift1[i].match)
std::cout << " -";
else if (err<100.0f)
std::cout << " +";
else
std::cout << " ";
std::cout << j << ":" << sum << ":" << (int)sqrt(err) << ":" << sift2[j].scale << ":" << (int)sift2[j].orientation << std::endl;
}
}
std::cout << std::endl;
if (found)
numFound++;
}
std::cout << "Number of founds: " << numFound << std::endl;
}
void PrintMatchData(SiftData &siftData1, SiftData &siftData2, CudaImage &img)
{
int numPts = siftData1.numPts;
#ifdef MANAGEDMEM
SiftPoint *sift1 = siftData1.m_data;
SiftPoint *sift2 = siftData2.m_data;
#else
SiftPoint *sift1 = siftData1.h_data;
SiftPoint *sift2 = siftData2.h_data;
#endif
float *h_img = img.h_data;
int w = img.width;
int h = img.height;
std::cout << std::setprecision(3);
for (int j=0;j<numPts;j++) {
int k = sift1[j].match;
if (sift1[j].match_error<5) {
float dx = sift2[k].xpos - sift1[j].xpos;
float dy = sift2[k].ypos - sift1[j].ypos;
#if 0
if (false && sift1[j].xpos>550 && sift1[j].xpos<600) {
std::cout << "pos1=(" << (int)sift1[j].xpos << "," << (int)sift1[j].ypos << ") ";
std::cout << j << ": " << "score=" << sift1[j].score << " ambiguity=" << sift1[j].ambiguity << " match=" << k << " ";
std::cout << "scale=" << sift1[j].scale << " ";
std::cout << "error=" << (int)sift1[j].match_error << " ";
std::cout << "orient=" << (int)sift1[j].orientation << "," << (int)sift2[k].orientation << " ";
std::cout << " delta=(" << (int)dx << "," << (int)dy << ")" << std::endl;
}
#endif
int len = (int)(fabs(dx)>fabs(dy) ? fabs(dx) : fabs(dy));
for (int l=0;l<len;l++) {
int x = (int)(sift1[j].xpos + dx*l/len);
int y = (int)(sift1[j].ypos + dy*l/len);
h_img[y*w+x] = 255.0f;
}
}
int x = (int)(sift1[j].xpos+0.5);
int y = (int)(sift1[j].ypos+0.5);
int s = std::min(x, std::min(y, std::min(w-x-2, std::min(h-y-2, (int)(1.41*sift1[j].scale)))));
int p = y*w + x;
p += (w+1);
for (int k=0;k<s;k++)
h_img[p-k] = h_img[p+k] = h_img[p-k*w] = h_img[p+k*w] = 0.0f;
p -= (w+1);
for (int k=0;k<s;k++)
h_img[p-k] = h_img[p+k] = h_img[p-k*w] =h_img[p+k*w] = 255.0f;
}
std::cout << std::setprecision(6);
}